Today various kinds of electronic systems such as industrial computers, work stations, desktop computers, laptop computers, cell phones etc. rely on a decades old device, an optical mouse, to sense the movement of the operator's hand (or finger, or something of equivalent function), and translate that movement into instruction(s) or motion vector(s) of the cursor(s) in the display of the electronic system. Inside each optical mouse lies an image sensor to capture series of images and compare them at a high frame rate. There are several factors affecting the performance of the image sensor, e.g. photodiode size (i.e. pixel size), resolution (e.g. pixels/inch), frame rate, lens quality, the intensity or incident angle of the illuminating light, etc. In the optical mouse industry, resolution is defined by the number of pixels that the image sensor and lens can view per inch while the mouse is being moved. If the resolution is high, then the operator would require less mouse movement to get accurate motion vector data, and this in turn will relax the requirement for higher frame rate, which eventually lowers the power consumption of the optical mouse. Today most of the mice run at frame rate of thousands per second, and at a resolution of 700-800 pixels per inch. Gaming mice have a higher resolution (e.g. thousands of pixels per inch) as compared to that of normal mice for a smoother and more accurate operation. The above specifications are satisfactory for most household users where the desktop surface is a wood plate, but when the optical mouse is facing a very smooth surface (e.g. a glossy plate), it becomes clumsy, slow, and often leads to unstable results. Therefore, a lot of power is wasted due to many of calculations, which only provide erroneous results.
FIG. 1 shows a conventional optical mouse 102 having a select button 101 and an USB cable 105 to connect to a computer. A monochromatic light source 103 is mounted in the cavity 106. By reflection, light from light source 103 impinging onto the targeted desktop surface 107 is captured by the image sensor 104.
FIG. 2 shows an exemplary case of how a particle on a surface under an optical computer mouse is seen by the image sensor 104. The particle surface is largely represented by pixels 201, 204, 205, etc. The particle edge is largely represented by pixel 202. It is to be noted that the difference in pixel values (i.e. the gray level) between pixel 201 and pixel 205 is usually smaller than that of pixels 202 and 203. Thus, for the best result of pattern recognition, it is desired to recognize the boundary, sharp tip, etc. by optical means. In order to reach this goal, a previous effort resorted to lighting techniques to make the object (i.e. surface textures, particles) stand out more from the background. The theory is the following: In materials science, the roughness of a surface is often denoted by an Ra value (specifically, roughness Ra is quantified by the arithmetic average of the vertical deviations (i.e. yi) of a real surface from its ideal form, which is expressed mathematically as
      R    a    =                    1        n            ⁢              ∑        1        n              ⁢                  |          y      i        |    .  Surface roughness has fundamental influence on microscopic images in that it forms microscopic shadows for the tiny objects that stand “extruded” out of the targeted surface plane. When there are distinctive shadows in the image, it is easier for the image sensor to see the objects.
FIG. 3A shows an image taken by a conventional optical mouse that is illuminated by a tilted light (e.g. approximately 45 degree to the targeted object surface). The shadow of the particle is represented as Pixel P1, P2, and P3. Pixel P4 represents the top surface of the object. Note that the contrast between P1, the shadow, and P5, the pixel representing the background, is usually larger than that of top surface of the object, P4. In fact, to the best performance of these types of optical mice, P4 is preferred to have as little variation as possible. In order to reach the goal of having the highest contrast for shadow and the lowest one for the object top surface. A second light source can be a diffused light beam that shines on the pixel plane P4. Since this light beam is preferred to be a diffused one; it is intended to form a “flat” image of the object surface and not used for pattern recognition and background; therefore, the variation in pixel values in the respective areas is very little.
As the above cases illustrate, today's optical mouse uses monochromatic light as a conventional mean to illuminate object, and this technique has lasted for decades. As a consequence seeing a color image has not been a requirement for the conventional optical mouse. Instead, it is the capability of seeing the shadows or textures in the image that is the most important to the performance of the conventional optical mouse.
U.S. Patent Application No. 2009/0160772 A1 (DePue et al.) is directed to an optical mouse with diffused optics, wherein an optical diffuser is configured to diffuse light from the light source that illuminates the tracking surface. Despite that this works well in ordinary situations in the extreme occasions when the surface of the targeted object is very smooth (i.e. Ra is too low), the approach fails in that there just are no or too few shadows available for the optical mouse to see at all.
There are some special designs to drastically increase the brightness of the particles or textures on object surface by enhancing the light intensity by laser light source. There are other approaches that use dark field image to make the background looked dimmed, and there are approaches that use a special angle of incident light to shine on the object surface in hopes that the PSNR is enhanced (PSNR stands for the peak signal to noise ratio). This is not only associated with the surface roughness Ra, but also the spectral response of the object surface. In conventional optical mouse device, the ratio of the intensity of the light beam coming from the targeted objects to that of the background light can be interpreted as the signal to noise ratio of the picture. Alternatively, the mouse industry use a similar meaning factor called the SQUAL, which denotes the surface quality. SQUAL counts the number of features identified by an image frame. If the signal level is increased caused by increasing the light intensity, or the background signal is suppressed by some diffusion means to a flat level with less undulation then the PSNR is increased. So, many of the conventional optical mice endeavor to increase the PSNR by, for example, adjusting the tilting angle of incident light timely, or using multiple light beams, etc. U.S. Pat. No. 7,439,954 B2 (Theytaz et al.) is directed to a multi-light source computer pointing device. U.S. Pat. No. 6,392,632 (Lee) is directed toward an optical cursor controlling device comprising an integrated camera. U.S. Patent Application No. 2005/0024336 (Xie et al.) is directed to the use of a Lambertian surface in a computer mouse to form a spectral reflection, which provides an enhanced contrast to the image for purposes of navigation. U.S. Patent Application No. 2005/0024623 (Xie et al.) is directed to the use of a Lambertian surface and a narrow bandwidth of light in a computer mouse to form a narrow bandwidth spectral reflection. U.S. Pat. No. 5,825,945 (Stolis et al.) is directed to a check imaging device using a Lambertian surface to project a highly uniform and diffused beam to an imaging site.
FIG. 3B demonstrates the drawback in the conventional art, when an optical computer mouse views the contour of an object on a desktop surface. When the targeted desktop surface has a very low surface roughness value or is made of a glossy material, the number of pixels representing the shadows or a unique point is rarified (i.e. P6A and P6B); wherein the total number has been decreased from three to two pixels comparing FIG. 3B to FIG. 3A. Also note that the contrast of the gray level among P6A and P6A (i.e. the shadow). P7 (the background scene), and P8 (the object body) has been decreased drastically. These effects often lead to the erroneous result of motion detection where the gray level denotes the energy density that a pixel receives from light impingement which can be monochromatic or multi-colored, depending on the sensitivity of the respective pixel.